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Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, and South Africa)

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The report covers every single prospect in the market structure analysis to represent how the various segments of the global Big Data Analytics In Defense and Aerospace market are progressing in terms of consumption, production, revenue, volume, and other noteworthy factors. The researchers have segmented the global Big Data Analytics In Defense and Aerospace market by product, application, and geography.

Edtech and big data firm Civitas Learning knows a thing or two about what’s working … What do you think will be the next big tech trend in your industry? … and using predictive analytics software to support students, but they will not …

One of the quickest ways for a company to fade into obscurity is to remain stagnant. This holds especially true for the tech industry, where companies are expected to adapt to trends at lightning speed. These six Austin companies are well aware of the consequences that come with getting too comfortable and have instead opted for a path of ongoing research and reinvention. Here’s how they stay ahead.

Edtech and big data firm Civitas Learning knows a thing or two about what’s working — and what’s not — in higher education. One major shift that co-founder and SVP of Product and Strategy Laura Malcolm noted is the industry’s move away from descriptive and predictive analytics in favor of prescriptive ones.

How has Civitas Learning set itself apart as a leader in your industry?

With a rigorous focus on improving student success outcomes such as persistence and graduation rates. We do this by providing machine learning software and user-centered product design focused on driving and measuring those outcomes. In particular, our software packages sophisticated predictive models and analytics into intuitive, actionable insights for student support staff while also using proprietary statistical software to measure results by creating on-the-fly control groups.

What do you think will be the next big tech trend in your industry?

An emerging trend in the use of analytics in education is moving from descriptive and predictive to prescriptive analytics. There is a growing trend of institutions adopting and using predictive analytics software to support students, but they will not meet the full potential of the technology until software is prescribing the right actions, supports and interventions, based on what works. We are working directly with the market to not only understand the kinds of actions and supports that are available, but measuring them to understand what works, and for which students, so that effective prescriptions can be offered.

By building technology designed for convenience and personalization for its end users, MVF has established itself a leader in marketing tech. CEO of MVF U.S. Bjorn Zellweger highlighted what makes their platform unique and how MVF plans on staying ahead of the curve.

Our tech applications allow us to run over 40 marketing channels and carefully blend and control traffic.”

How has MVF set itself apart as a leader in your industry?

Our proprietary technology platform is what gives MVF its competitive edge. On the client side, our unique tech applications allow us to run over 40 marketing channels and carefully blend and control traffic to meet the requirements of our clients in terms of timing, volume and quality. For the customers we generate, our proprietary Capture platform enables us to optimize our forms in real time and interact with different buyer segments in the way that best suits their needs, including chatbots, SMS, email and on-form appointment booking.

What do you think will be the next big tech trend in your industry?

Using machine learning and data to enhance user experience and introduce more personalization is a key focus for us. We already have tech that is able to predict and tailor the way users interact with us, choosing the solution that best suits their requirements. Using the signals they send enables us to increase the quality of leads for our clients and help our users get their quotes in a truly personal way.

It’s a really exciting and constantly evolving area, and we’re investing in more types of personalization as the landscape of how users interact with technology continues to expand.

International real estate firm Keller Williams saw one its largest years of sales last year, thanks in part to its investment in technology. Neil Dholakia, chief product officer, said the secret sauce to its recent and future successes resides in its research and development processes within KW Labs, the company’s innovation hub.

We were the first in our industry to come to market with a fully connected, smart real estate cloud.”

How has Keller Williams set itself apart as a leader in your industry?

We were the first in our industry to come to market with a fully connected, smart real estate cloud that incorporates and manages all aspects of an agent’s business. What makes our platform smart is our proprietary, award-winning artificial intelligence layer, which we call Kelle. Our platform uses the latest in enterprise-level technology from microservices to progressive web apps on Google Cloud, all infused with artificial intelligence and machine learning.

What do you think will be the next big tech trend in your industry?

It’s all about platform integration in the real estate industry. We are focused on consolidating all aspects of the real estate transaction onto one platform, and that involves integrating with mortgage, title, insurance and property management companies to provide a seamless consumer experience within our ecosystem. We plan to get there first. And set the bar high.

Jason Vertrees, Volusion’s VP of engineering and data science, said their e-commerce platform is all about ease of use for the customer. While it looks simple on the front end, what’s happening under the hood is quite complex. Vertrees told us more about Volusion’s machine learning engine, which runs off 5,000 data requests per second.

Keeping things simple has helped Volusion grow throughout the years.”

How has Volusion set itself apart as a leader in your industry?

We’ve always focused tightly on making merchants — we call them “founders” — successful. Being a founder isn’t easy; we’re here to support them each step along their entrepreneurial path. Our platform is simple to use, so it reduces the cognitive load on busy founders just trying to get things done. Keeping things simple has helped Volusion grow throughout the years.

What do you think will be the next big tech trend in your industry?

Data-driven automation will continue to expand into commerce, further optimizing the shopper experience and increasing revenue. Volusion’s systems serve over 5,000 requests per second, providing enough data to fuel real-time machine learning applications which make recommendations back to our founders and shoppers. Data-driven insights, paired with automation, will free up merchants’ time for more important tasks, like focusing on the customer and getting the product right.

A customer-centric approach has helped identity governance provider SailPoint stand out in a sea of rising competition, said CMO Juliette Rizkallah. To stay on top, the Austin-based company, which launched in 2004, has implemented technologies like machine learning and AI into its solutions.

We are a customer-centric organization, and we keep a constant pulse on their needs as we evolve our products.”

How has SailPoint set itself apart as a leader in your industry?

SailPoint has been paving the way in identity governance for more than a decade. We have always set ourselves apart by understanding what customers need and delivering on it. Further, we are a customer-centric organization, and we keep a constant pulse on their needs as we evolve our products.

What do you think will be the next big tech trend in your industry?

Machine learning and artificial intelligence have evolved from buzzwords to reality in the tech and security industries. We are now seeing many of these technologies take off in today’s organizations. With our analytics solution, IdentityAI, we are enabling organizations to harness that technology in their identity programs, allowing them to govern their digital identities smarter.

The future of home buying will likely follow the habits and practices of millennials. With that in mind, Modernize VP of Engineering Andy Michaelis said his team continues to create products that cater to a generation that prefers to communicate online.

We build products to make working with contractors easier.”

How has Modernize set itself apart as a leader in your industry?

Home improvement projects can often be costly and stressful, so we build products to make working with contractors easier. A few years ago, we moved to an API-first infrastructure enabling us with Docker to automate our testing and feature branch deployments that now occur dozens of times a day. This foundation has enabled us to quickly innovate on our products, providing homeowners with tools like cost calculators, contractor feedback, profiles and enabling the matching process to be as frictionless as possible.

What do you think will be the next big tech trend in your industry?

I think as millennials start to purchase their first homes, they are going to be more tech savvy than we’ve ever seen before. We continue to build products that work for them based on how they want to be communicated with, and enable everything from texting with contractors to booking an entire roof replacement online.

Through automation, IRI’s analytic solutions, with advanced statistical … the best opportunities — is revolutionizing our ability to leverage big data to …

CHICAGO–(BUSINESS WIRE)–Mar 13, 2019–IRI ®, a global leader in innovative solutions and services for consumer, retail and media companies, today announced artificial intelligence (AI) and machine learning enhancements that are changing the way clients gather insights and prescriptive analytics from IRI’s leading suite of solutions. IRI has invested nearly $1 billion in its technology over the past several years to enable its solutions to automatically identify market opportunities and proactively provide recommendations to clients to enable decisions. These technological advancements facilitate a suite of always-on solutions, that provide the industry’s most robust, granular insights, with unprecedented speed.

“IRI’s unparalleled, granular data assets, including frequent shopper card data, provides endless opportunity, but only if you have the proper technology to mine this universe of data points to enable key decisions,” said Krishnakumar (KK) Davey, president of IRI Strategic Analytics. “As our vast data assets continue to grow, it has become more difficult and time-intensive for a decision maker to manually test enough hypotheses to find the most relevant and impactful insights that drive sales and marketing decisions. That’s why IRI has integrated AI and machine learning into our full suite of analytic solutions so that the technology does the heavy lifting automatically.”

Through automation, IRI’s analytic solutions, with advanced statistical modeling routines as the foundation, can explore and compare a multitude of scenarios offline, automatically scour through thousands of possibilities, and identify top opportunities that deserve further exploration. These key opportunities are summarized on IRI’s easy-to-use Unify® visualization platform and quickly made available to IRI’s clients via alerts and recommendation engines. Users can define and customize rules engines to ensure reasonable and realistic scenarios are executed by the machine, and only relevant recommendations are pushed to the user. Users can also create alerts to ensure they are immediately notified about any situations that meet a pre-defined range or target.

Davey continued, “This change in orientation – from laborious manual exploration to having machines automatically identify the best opportunities — is revolutionizing our ability to leverage big data to drive growth. By integrating AI and machine learning across our leading suite of solutions, IRI has taken a clear leadership position in powering the path forward for the industry.”

IRI is leveraging AI and machine learning to enhance a variety of its analytic solutions, including:

IRI Aisle Optimization: Recommends optimal layouts for the composition of product categories and the space of each category to improve sales productivity.

To learn more about IRI’s solutions and the way they help clients leverage the latest in big data, machine learning, and artificial intelligence to deliver insights and drive growth, contact Nagi Jonnalagadda at Nagi.Jonnalagadda@IRIworldwide.com.

About the IRI Partner Ecosystem

IRI fundamentally believes that delivering differentiated growth for clients requires deep, highly integrated partnering with a variety of best-of-breed companies. As such, IRI works closely with a broad range of industry leaders across multiple industries and sectors to create innovative joint solutions, services and access to capabilities to help its clients more effectively collaborate and compete in their various markets and exceed their growth objectives. IRI is committed to its partnership philosophy and continues to actively enhance its open ecosystem of partners through alliances, joint ventures, acquisitions and affiliations. The IRI Partner Ecosystem includes such leading companies as 84.51°, Adobe, The Boston Consulting Group, Clavis Insights, comScore, Data Plus Math, Edison, Experian, GfK, Gigwalk, Google, Ipsos, Jumpshot, Mastercard Advisors, MaxPoint, MFour, Omnicom, One Click Retail, Oracle, Pinterest, Research Now/SSI, Simulmedia, SPINS, Univision, Viant and others.

About IRI

IRI is a leading provider of big data, predictive analytics and forward-looking insights that help CPG, OTC health care organizations, retailers, financial services and media companies grow their businesses. A confluence of major external events — a change in consumer buying habits, big data coming into its own, advanced analytics and personalized consumer activation — is leading to a seismic shift in drivers of success in all industries. With the largest repository of purchase, media, social, causal and loyalty data, all integrated on an on-demand, cloud-based technology platform, IRI is empowering the personalization revolution, helping to guide its more than 5,000 clients around the world in their quests to remain relentlessly relevant, capture market share, connect with consumers, collaborate with key constituents and deliver market-leading growth. For more information, visit www.iriworldwide.com.

Data generated in the oil and gas industry growing in terms of diversity, volume and speed. Therefore, new technologies are needed to interpret and …

Data generated in the oil and gas industry growing in terms of diversity, volume and speed. Therefore, new technologies are needed to interpret and integrate large amounts of data available in both structured and unstructured ways. Because this data is regularly generated from multiple sources, such as geological data, seismic data, well-recorded data, and other data, the need for a systematic system for such data analysis is growing. Various information technology providers are working diligently to create solutions that can create new opportunities to capture large data markets.

The global Big Data and Analytics in Oil and Gas market is projected to rise at a healthy +16% CAGR throughout the forecast period between 2019 and 2026.

Research N Reports.com announces the obtainability of a new report in its repository, titled “Global Big Data and Analytics in Oil and Gas Market Research Report 2019.” The report represents the current scenario of the market, and based on in-depth study of all the major factors that are estimated to effect the demand in the forecast period, it estimates the state of the Big Data and Analytics in Oil and Gas market by 2026. The report takes stock of the Big Data and Analytics in Oil and Gas market on the basis of its attractiveness as well as investment feasibility. It also offers quantitative and qualitative description of every aspect of the market and catches the emerging industry trends. The aim of the report is to enable the readers to focus on the Big Data and Analytics in Oil and Gas market on the basis of product specifications, existing competitive landscape and the market’s revenue with profitability.

As per the findings, the report has detected that the Big Data and Analytics in Oil and Gas market is marked by several segments. The players in the global Big Data and Analytics in Oil and Gas market are directed to understand the diverse and dynamic regulatory restrictions and plot their expansion strategies accordingly.

Geographically, the report explores the potential of the Big Data and Analytics in Oil and Gas market in the regions of North America, Europe, and Southeast Asia as well as in the countries of China, Japan, and India. Moreover, the countries generating high revenue in these regions have also been analyzed along with exhaustive coverage of developments and innovation in these countries. Currently, North America and Europe serve the maximum demand for Big Data and Analytics in Oil and Gas, however, emerging economies such as India and China are expected to turn in to highly profitable country-wide markets. These two Asia Pacific countries are vastly populated, and are among the most promising emerging economies with increasing disposable income in the urban population.

For each of the region and country-wide markets, the report explores the production capacity, price and gross margin, taking historical data from 2012 until 2018. To comprehend the competitive consequence among the manufacturers, the report evaluates the market share, capacity, production, average price of some of the leading companies in 2016 and 2018. It also identifies the top three and top five manufacturers as of 2018, and studies their recent strategic decisions such as mergers and acquisitions and expansion plans.

The report also offers extensive research on the key players in this market and detailed insights on the competitiveness of these players. The key business strategies such as mergers & acquisitions, partnerships, collaborations, and contracts adopted by the major players are also identifies and analyzed in the report. For each company, the report recognizes their manufacturing base, competitors, product type, application and specification, pricing, and gross margin.

Analytics & Data Science In Indian Financial Sector – A Deep Dive 2019 … This includes a small number of companies into products and a larger …

Over the last few years, financial institutions have achieved exponential growth, driving innovation in the sector by building enterprise-wide analytics capability, that is now woven into the key business processes throughout the organisation. Much of the growth in analytics jobs is also credited to the fintech boom in India – led by top digital payments firms Paytm and PhonePe that leverage data analytics to not only digitize cash payments but also scale the reach of their customers.

The emerging fintech ecosystem in India has created a slew of opportunities in data analytics and AI space. On the other end of the spectrum is tremendous innovations happening in the Financial Services (FS) organisations space with banks and financial institutions applying advanced analytics and machine learning across the entire business model. Today, banking and financial services industry has adopted analytics across three broad functional areas – customer satisfaction, risk management and operations analytics.

Our annual study done by Jigsaw Academy and AIM captures the data-heavy financial ecosystem in India and dives into the talent market — unpacking key trends across jobs, salaries, hiring trends, top financial companies in India hiring financial analytics talent and the AI talent divide across companies. The research also reveals what’s hampering the growth and innovation story is the big talent challenge facing financial institutions.

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Key Trends

The size of the analytics industry in the financial sector is currently estimated to be $1.2 billion (annual) in revenue

Currently, there are approximately 60,000 data science and financial analytics professionals in India, working in the finance sector

According to our research, 7,000 freshers were added to the financial analytics workforce in India in 2018

Mumbai continues to be the financial hub with 33% analytics professionals working in the financial capital

The median financial salary is India is INR 13.4 lakh across all experience level and skillset

On average, the entry-level salary for financial analytics professionals is less than INR 6 lakh while 3% of financial analytics workforce takes home more than INR 50 lakh

Women participation is skewed with only 27% of women making up the financial analytics workforce in India

Close to 250 companies in India work on financial analytics in some form. This includes a small number of companies into products and a larger chunk offering either offshore, recruitment or training services

Moreover, the number of vertical financial analytics companies in India is less as compared to North America and Asia Pacific. India accounts for just 7% of global Analytics companies

Company Size

On average, Indian financial analytics companies have 340 employees on their payroll

Almost 88% of financial analytics companies in India have less than 200 employees.

Analytics Talent Divide Across Companies

Almost 59% of financial analytics professionals in India are employed with large-sized companies(with a total employee base of 10k+)

Mid-size organizations (total employee base in the range of 200-10K) employ 30% of all financial analytics professionals in India

A large percentage of financial analytics professionals are absorbed by large service providers or MNC captive units

This is also a clear indication of the financial analytics talent divide between enterprises and startups in India, which will only continue to widen further

Financial Hubs in India

41% of all companies that work on financial analytics in India are based out of Mumbai, the financial capital of India

This is followed by Bengaluru at 18%

Financial Analytics Jobs & Salaries in India

The median financial analytics salary in India is INR 13.4 Lakhs across all experience level and skill sets.

Around 36% of financial analytics professionals in India have an entry-level salary of less than 6 Lakh

Almost 3% of financial analytics professionals in India command a salary higher than 50 lakh

While it is difficult to ascertain the exact number of open financial analytics job openings, according to our estimates, close to 36,000 positions related to financial analytics are currently available to be filled in India

The top skill sets that financial analytics employers are looking for are Data Analytics, Marketing Analytics, Predictive Modeling, Business Analytics, SAS, Campaign Management & Business Intelligence

Financial Analytics Jobs By Cities

In terms of cities, Mumbai accounts for around 28% of financial analytics jobs in India.

Delhi/NCR comes very close second contributing 28% jobs in India.

Approximately 21% of financial analytics jobs are from Bengaluru

Key Takeaways

Innovation Drivers in the Financial Ecosystem

As banks and financial institutions transform to become data-driven enterprises, digital technology will soon become the backbone of FIs

In order to build a sophisticated analytics capability, banks and FIs are now investing along several important dimensions – technology infrastructure, strengthening processes and people

Another key area emerging is banks and major FIs are setting up dedicated analytics and AI CoEs in strategic partnerships with fintech and knowledge mentors to drive the innovation story forward

Increasingly, the financial industry has started leveraging in-built analytics, machine learning and AI capabilities for specific use cases to drive profitability and growth

Rethinking Talent Strategies

The key traits financial institutions look for when hiring talent are: quantitative and technical skills as well business acumen to generate insights. The core capabilities required are ability to use statistics, quantitative analysis and information-modelling techniques to make business decisions

There’s also a fundamental rethink in terms of people strategy with most FS organisations in India fostering a culture of innovative thinking and embracing hacks for hire to bolster their human capital.

In order to meet the growing talent demand, financial organisations are investing in developing robust learning modules and skill development programmes to reskill staff

Most leading financial organisations are now taking an active step and partnering with third-party institutions to train and source talent. This is in a way, is paving the way for talent exchanges

Corporate Training As A Key Indicator of Changing Trends in the Financial Sector

There has been a significant shift in mindset when in comes to upskilling. Earlier the focus was on the upskilling of a few isolated people in a core data science team. However, organisations have now begun to realize that in order to derive competitive advantage from data, every employee must become data literate and “data smart”. There has been a strong demand for analytics training across levels and training at scale. Taking a top-down approach, this has spanned across an appreciation program for senior leadership, followed by a more hands-on training for the data enabled roles (basically, anyone in the organization who has access to or works with any kind of data) and finally, specialized and more advanced training for the existing data science team.

Functions across banking and finance (risk, marketing, operations, collections, regulation, governance, reporting etc) have begun to increasingly rely on big data analytics to optimize their performance. This has resulted in an increasing demand for data scientists who are highly specialized. In particular, Machine Learning has become a dominant force and there is significant demand for hyper-specialized skills in Machine Learning and Deep Learning.

The emergence of the analytics hub, like a centre of excellence for analytics. The hub consists of a pool of data scientists who work across functions and do the heavy lifting. A centralized team puts the data scientists in a large group where best practices are easy to share and every data scientist is exposed to new skills a lot faster than when they are in smaller, siloed teams. Typically, the smaller, faster, usually non-strategic kinds of analyses can be done within the smaller, internal teams and bigger,more strategic analysis goes to the centralised team.

Way Forward

Judging the impact of artificial intelligence and automation on job roles and skill-set, and how it will redesign jobs frameworks, (for eg. AI’s robo-advisors have replaced financial advisors), FS organsiations are now doubling down on closing the talent gap by collaborating with leading institutes and stakeholders to even out the supply and demand gap. In an automated world, financial organisations have recognized the changing skills demand and in order to keep pace with the market, organisations are teaming up with stakeholders to develop tailored solutions for talent management and develop work-ready workforce.